{ \renewcommand{\arraystretch}{1.2} 
\begin{table} 
\center 
\begin{tabular}{cc ccc } 
 Method & &  $\mu$ & $\phi$ &$\sigma^2$ \\ \hline  \hline
\rowcolor{LightCyan} 
DA & Mean 
 & 0.3764  & 0.9619  & 0.0807  \\  [0.75ex] 
 & (Std) 
 & (0.1155)  & (0.0062)  & (0.0111)  \\  [0.75ex] 
 [111.83 s] & ESS 
 & 3201.6954  & 114.2589  & 63.4271  \\  [0.75ex] 
\rowcolor{LightCyan} 
Adapt10 & Mean 
 & 0.3816  & 0.9618  & 0.0864  \\  [0.75ex] 
 & (Std) 
 & (0.1163)  & (0.0065)  & (0.0133)  \\  [0.75ex] 
 [1980.48 s] & ESS 
 & 5398.2000  & 249.4021  & 135.9168  \\  [0.75ex] 
\rowcolor{LightCyan} 
Adapt20 & Mean 
 & 0.3787  & 0.9611  & 0.0854  \\  [0.75ex] 
 & (Std) 
 & (0.1152)  & (0.0065)  & (0.0127)  \\  [0.75ex] 
 [2290.29 s] & ESS 
 & 5440.1547  & 279.2726  & 143.2475  \\  [0.75ex] 
\rowcolor{LightCyan} 
Adapt30 & Mean 
 & 0.3764  & 0.9613  & 0.0844  \\  [0.75ex] 
 & (Std) 
 & (0.1148)  & (0.0064)  & (0.0121)  \\  [0.75ex] 
 [2566.66 s] & ESS 
 & 5784.0931  & 120.8229  & 60.6565  \\  [0.75ex] 
\rowcolor{LightCyan} 
Bin20 & Mean 
 & 0.3814  & 0.9618  & 0.0817  \\  [0.75ex] 
 & (Std) 
 & (0.1165)  & (0.0064)  & (0.0120)  \\  [0.75ex] 
 [1683.02 s] & ESS 
 & 4504.0119  & 239.6980  & 147.4086  \\  [0.75ex] 
\rowcolor{LightCyan} 
Bin30 & Mean 
 & 0.3783  & 0.9618  & 0.0813  \\  [0.75ex] 
 & (Std) 
 & (0.1155)  & (0.0064)  & (0.0119)  \\  [0.75ex] 
 [2056.75 s] & ESS 
 & 5484.1997  & 301.2721  & 167.7196  \\  [0.75ex] 
  \hline 
\multicolumn{5}{p{6cm}}{\footnotesize{ESS: at lag equal to the lowest order at which sample autocorrelation is not significant.}}  \\ 
\multicolumn{5}{p{6cm}}{\footnotesize{Computing times  (in seconds) in square brackets.}}  \\ 
\end{tabular}
 \caption{SV model: posterior means, standard deviations and effective sample sizes (ESS) of the model parameters for $M=50000$ posterior draws after a burn-in of $10000$.}
\label{tab:SV_results_theta_IBM}  
\end{table}
}} \normalsize